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How Moving Apigee Sense to GCP Reduced Our “Data Litter”

SridharR
Jan 30, 2018

In the year-plus since Apigee joined the Google Cloud family, we’ve had the opportunity to deploy several of our services to Google Cloud Platform (GCP). Most recently, we completely moved Apigee Sense to GCP to use its advanced machine learning capabilities. Along the way, we also experienced some important performance improvements as judged by a drop in what we call “data litter.”

In this post, we explain what data litter is, and our perspective on how various GCP services keep it at bay. Through this account, you may come to recognize your own application, and come to see data litter as an important metric to consider.

First, let’s take a look at Apigee Sense and its application characteristics. At its core, Apigee Sense protects APIs running on Apigee Edge from attacks and unwanted exploitation. Those attacks are usually performed by automated processes, or "bots," which run without the permission of the API owner. Sense is built around a four-element "CAVA" cycle: collect, analyze, visualize and act. It enhances human vigilance with statistical machine learning algorithms.

We collect a lot of traffic data as a by-product of billions of API calls that pass through Apigee Edge daily. The output end of each of the four elements in the CAVA cycle is stored in a database system. Therefore, the costs, performance and scalability of data management and data analysis toolchains are of great interest to us.

Read the whole story on the Google Cloud Platform blog

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